Abstract. Algorithm selection is typically based on models of algorithm performance learned during a separate offline training sequence, which can be prohibitively expensive. In r...
This paper deals with test case selection from axiomatic specifications whose axioms are quantifier-free first-order formulae. Test cases are modeled as ground formulae and any spe...
An important drawback to the popular Belief, Desire, and Intentions (BDI) paradigm is that such systems include no element of learning from experience. In particular, the so-calle...
This paper introduces a gestural perceptual-based approach to select objects, i.e., nodes and/or edges along paths. Based on known results from perception research, we propose a mo...
In semi-supervised clustering, domain knowledge can be converted to constraints and used to guide the clustering. In this paper we propose a feature selection algorithm for semi-s...